Merging data frames without duplicating data when several matches are possible

I need merge two data frames, without having duplicate rows/duplicated data if there is more than one match. Basically, if the matching between my dataframes is ambiguous, I would like the ambiguous rows to NOT be matched, and each row to remain separate instead.
I've been using the merge function, but it states that If there is more than one match, all possible matches contribute one row each, and I got to the same result using join/inner_join functions. Is there a way to fix this ?

Example:

df1

df2

What I get using merge by ID

What I want

Thank you for your help !

You can try to identify the duplicated id's, exclude them when using merge and rbind them afterwards.

X <- unique(c(df1$ID[duplicated(df1$ID)], df2$ID[duplicated(df2$ID)]))
plyr::rbind.fill(merge(df1[!df1$ID %in% X,], df2[!df2$ID %in% X,]),
                 df1[df1$ID %in% X,],
                 df2[df2$ID %in% X,])
#  ID Question1 Question2 Question3 Question4
#1 A1         1         2         a         b
#2 B1         3         4         c         d
#3 C1         5         6      <NA>      <NA>
#4 C1         7         8      <NA>      <NA>
#5 C1        NA        NA         e         f
#6 C1        NA        NA         g         h

Data

df2 <- read.table(header=TRUE, text="ID 	Question3 	Question4
A1 	a 	b
B1 	c 	d
C1 	e 	f
C1 	g 	h")

df1 <- read.table(header=TRUE, text="
ID 	Question1 	Question2
A1 	1 	2
B1 	3 	4
C1 	5 	6
C1 	7 	8")

I always seek to avoid many to many merges by creating a case variable for each duplicate id and then merge by ID case.

Like below:

df1 <- data.frame(ID = c("A1", "B1", "C1", "C1"), Q1 = c(1, 3, 4, 7), Q2 = c(2, 4, 6, 8))
df2 <- data.frame(ID = c("A1", "B1", "C1", "C1"), Q3 = c("a", "b", "c", "d"), Q4 = c("b", "d", "f", "h"))
library(dplyr)

df3 <- full_join(df1, df2, by = "ID")

df3

df11 <- df1 %>%
  group_by(ID) %>%
  mutate(case = row_number())

df22 <- df2 %>%
  group_by(ID) %>%
  mutate(case = row_number())

tmp <- df22 %>% summarise(count = n())

df22 <- merge(df22, tmp, by = c("ID"))

df22 <- df22 %>% mutate (case = ifelse(count==2,case+2,case))
df22

df33 <- full_join(df11, df22, by = c("ID", "case"))
df33

which returns: